Blockchain for open scientific research

ABSTRACT

Techniques facilitating using a blockchain system that integrates the trustworthiness of the blockchain concept with open scientific research by generating a blockchain of the experiments formed, data collected, analyses performed, and results achieved are provided herein. In an example, the blockchain system can form a blockchain representing a research project, wherein the blockchain comprises a first block of research data and a second block of analysis data representing a log of an analysis performed on the research data. Summary blocks and correction blocks can also be added to the blockchain representing the post analysis of the research results. One or more of the subsequent blocks can be linked to the preceding blocks using information in block headers that can also serve to determine whether modifications to the blocks have been performed.

BACKGROUND

The subject disclosure relates to integrating a blockchain and datacollection and analysis for open scientific research. Currently, thereare limited platforms that allow for sharing information aboutscientific research and showing transparent data collection and analysissteps. Platforms that do exist, lack the requisite controls andmechanisms to allow for trustworthy data, as there are few options forensuring that data will be resistant to modification.

For example, as described in Topol, Money Back Guarantees forNon-Reproducible Results, BMJ 2016, 353:i2770, published 24 May 2016, itis acknowledged that “[t]he problem of irreproducibility in biomedicalresearch is real and has been emphasized in multiple reports” and that“use of blockchain technology has recently been shown to provide animmutable ledger of every step in a clinical research protocol, and thiscould easily be adapted to basic and experimental model science. Allparticipants in the peer-to-peer research network have access to all ofthe time stamped, continuously updated data. It is essentially tamperproof since any change, such as to the pre-specified data analysis,would have to be made in every computer (typically thousands) within thedistributed network.” While Topol describes the problem of datatransparency and proposes that blockchain could serve as a solution. Itdescribes researchers as having access to time-stamped immutable datathrough a public blockchain. It does not describe 1) mixedconfidentiality policies, 2) researchers having access to real-time logsof analyses (only to changes to an analysis plan), 3) blockchain loggingof the analytical steps via connection of analytical software to ablockchain contract, 4) any methods or algorithms to assess thestatistical power of the underlying result by analysis of steps on theblockchain (for example, automatic correction for multiple analyses) or5) any integrated algorithms or blockchain contracts that performfunctions other than a) a public record of data transactions and b)refunds based on detection of a violation of data provenance.

Similarly, Irving et al., How Blockchain-Timestamped Protocols couldImprove the Trustworthiness of Medical Science, F1000Research 2016,5:222, last updated 31 May 2016 discloses a “report a proof-of-conceptstudy using a ‘blockchain’ as a low cost, independently verifiablemethod that could be widely and readily used to audit and confirm thereliability of scientific studies.” Similar to Topol above, Irving doesnot disclose points 1-5 above.

U.S. Pat. No. 7,404,079 to Gudbjartsson et al. discloses “an automatedsystem for the processing of data packets, composed of identifiers anddata, such that the personally identifiable data sent by one party maybe considered anonymous once received by a second party. The inventionuses secret sharing techniques to facilitate distributed key managementof the mapping functions and strong authentication to allow the systemto be operated remotely.” Gudjbjartsson discloses a mixed securitypolicy that could be an example of one that could be utilized as a priorcontract for the invention described here. However it is not the onlysuch security contract that could be used, and it differs from thesubject disclosure in that: 1) it is an up-front security contractbetween all parties, rather than a security policy defined by the aparty at the time they expose data to the blockchain; 2) it does notspecify a public blockchain ledger; 3) it does not name methods foranalyzing the ledger to assess the robustness of data; and 4) it doesnot specify a smart contract that treats reported or analyzed datadifferently from raw data.

SUMMARY

The following presents a summary to provide a basic understanding of oneor more embodiments of the invention. This summary is not intended toidentify key or critical elements, or delineate any scope of theparticular embodiments or any scope of the claims. Its sole purpose isto present concepts in a simplified form as a prelude to the moredetailed description that is presented later. In one or more embodimentsdescribed herein, systems, computer-implemented methods, apparatusand/or computer program products that facilitate synchronization ofprocessors for blockchain formation are described. The disadvantages ofthe references discussed above in the background have been resolved withthe features disclosed herein.

According to an embodiment, a computer-implemented method is provided.The computer-implemented method can comprise generating, by a deviceoperatively coupled to a processor, a first block from a first file,where the first block comprises a first header and experimental data iscomprised within the first file, where the first header furthercomprises a first time stamp, an identifier that identifies a source ofthe experimental data, and a first hash based on the experimental data;and generating, by the device, a second block based on a second filethat comprises a log of an analysis performed on the experimental data,wherein the second block comprises the log of the analysis and a secondheader that comprises a second time stamp, a link to the first block,and a second hash based on the log of the analysis. According to thisembodiment, an advantage is realized over the prior art because ablockchain is formed based on the data collected and analyses areperformed to provide a tamper resistant log of scientific research.

In an optional embodiment, the computer-implemented method furthercomprises: performing, by the device, a correction to the result of theanalysis based on a review of the summary of the experimental data ofthe third block; generating, by the device, a fourth block comprisingthe correction; and joining, by the device, the fourth block to theblockchain. According to this embodiment, an advantage is realized overthe prior art because the result of the analysis is corrected therebyresulting in greater reliability and accuracy.

In an optional embodiment, the computer-implemented method furthercomprises encrypting, by the device, the experimental data and the logof the analysis prior to forming the first block and second blockrespectively. According to this embodiment, an advantage is realizedover the prior art because the experimental data and the log of theanalysis is encrypted prior to forming the first and second blocksthereby increasing security and reducing opportunities for tamperingwith and/or otherwise altering such information.

In another embodiment, a system can comprise a memory that storescomputer executable components and a processor that executes thecomputer executable components stored in the memory. The computerexecutable component can comprise a data collection component thatcreates a master data block from a data entry blockchain, where the dataentry blockchain comprises a group of data entry blocks that are linkedto each other, and where the master data block comprises a first headerand data from the data entry blocks. The header can further comprise afirst time stamp, an identifier that identifies a source of the data,and a first hash based on the data. The computer executable componentscan also comprise an analysis component that creates an analysis blockcomprising log of an analysis performed on the data and a second headerthat comprises a second time stamp, a link to the master data block, anda second hash based on the log of the analysis, where the analysis blockand the master data block comprise a blockchain. According to thisembodiment, an advantage is realized over the prior art because ablockchain is formed based on the data collected and analyses areperformed to provide a tamper resistant log of scientific research.

In an optional embodiment, the computer executable components caninclude a correction component that rates a reliability of the result ofthe analysis based on the summary of the analysis and the log of theanalysis, where the reliability is associated with a number of attemptsto achieve the result of the analysis. This reliability rating is anadvantage over the prior art as it provides an objective basis fordetermining the amount of trust that should be placed in a result of thescientific research or in the conclusion reached.

In another embodiment, a computer-implemented method is provided. Thecomputer-implemented method can comprise forming, by a deviceoperatively coupled to a processor, a blockchain representing a researchproject, where the blockchain comprises a first block of research data,and a second block of analysis data representing a log of an analysisperformed on the research data. The computer-implemented method can alsocomprise forming, by the device, a summary block comprising a summary ofthe research data and summary of the analysis data. Thecomputer-implemented method can also comprise appending, by the device,the summary block to the blockchain. The summary block provided in thisembodiment can be added to the blockchain and represent conclusionsreached by researchers and provide a template for facilitatingpublishing a scientific paper on the research.

In another embodiment, a system can comprise a memory that storescomputer executable components and a processor that executes thecomputer executable components stored in the memory. The computerexecutable components can comprise: a data collection component that:receives a first file having experimental data; and generates a firstblock from the first file, where the first block comprises a firstheader and the experimental data, and where the header further comprisesa first time stamp, an identifier that identifies a source of theexperimental data, and a first hash based on the experimental data. Thecomputer-executable components can also comprise an analysis componentthat generates a second block based on a second file that comprises alog of an analysis performed on the experimental data, where the secondblock comprises the log of the analysis and a second header thatcomprises a second time stamp, a link to the first block, and a secondhash based on the log of the analysis; and an inspection component thatgenerates a third block comprising a summary of the experimental dataand the analysis and a result of the analysis. According to thisembodiment, an advantage is realized over the prior art because ablockchain is formed based on the data collected and analyses areperformed to provide a tamper resistant log of scientific research.

In an optional embodiment, the computer executable components furthercomprise a correction component that rates a reliability of the resultof the analysis based on the summary of the analysis and the log of theanalysis, wherein the reliability is associated with a number ofattempts to achieve the result of the analysis. According to thisembodiment, an advantage is realized over the prior art because thereliability of the result of the analysis is rated.

According to yet another embodiment, a computer program product togenerate a blockchain using open scientific data is provided. Thecomputer program product can comprise a computer readable storage mediumhaving program instructions embodied therewith. The program instructionscan be executable by a processor and cause the processor to generate amaster data block from a data entry blockchain, where the data entryblockchain comprises a group of data entry blocks that are linked toeach other, where the master data block comprises a first header anddata from the data entry blocks, and where the header further comprisesa first time stamp, an identifier that identifies a source of the data,and a first hash based on the data. The processor can also generate ananalysis block comprising a log of an analysis performed on the data anda second header that comprises a second time stamp, a link to the masterdata block, and a second hash based on the log of the analysis, wherethe analysis block and the master data block comprise a blockchain.According to this embodiment, an advantage is realized over the priorart because a blockchain is formed based on the data collected andanalyses are performed to provide a tamper resistant log of scientificresearch.

In an optional embodiment, the program instructions are furtherexecutable to cause the processor to rate a reliability of the result ofthe analysis based on the summary of the analysis and the log of theanalysis, wherein the reliability is associated with a number ofattempts to achieve the result of the analysis. According to thisembodiment, an advantage is realized over the prior art because thereliability of the result of the analysis is determined employing anevaluation of the summary of the analysis and the log of the analysis.

DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a high-level block diagram of an example,non-limiting blockchain system in accordance with one or moreembodiments described herein.

FIG. 2 illustrates another high-level block diagram of an example,non-limiting blockchain system in accordance with one or moreembodiments described herein.

FIG. 3 illustrates a flow diagram of an example, non-limiting method ofintegrating blockchain functionality with open scientific research inaccordance with one or more embodiments described herein.

FIG. 4 illustrates a block diagram of an example, non-limiting systemthat forms a data blockchain from separate sets of data in accordancewith one or more embodiments described herein.

FIG. 5 illustrates another block diagram of an example, non-limitingsystem that forms an analysis blockchain in accordance with one or moreembodiments described herein.

FIG. 6 illustrates another block diagram of an example, non-limitingopen research blockchain in accordance with one or more embodimentsdescribed herein.

FIG. 7 illustrates another block diagram of an example, non-limitingsystem of headers and data portions of a data blockchain in accordancewith one or more embodiments described herein.

FIG. 8 illustrates a flow diagram of an example, non-limitingcomputer-implemented method that forms a blockchain based on researchdata and analysis in accordance with one or more embodiments describedherein.

FIG. 9 illustrates another flow diagram of an example, non-limitingcomputer-implemented method that forms a blockchain based on researchdata and analysis in accordance with one or more embodiments describedherein.

FIG. 10 illustrates a block diagram of an example, non-limitingoperating environment in which one or more embodiments described hereincan be facilitated.

FIG. 11 illustrates a block diagram of an example, non-limiting cloudcomputing environment in accordance with one or more embodiments of thepresent invention.

FIG. 12 illustrates a block diagram of example, non-limiting abstractionmodel layers in accordance with one or more embodiments of the presentinvention.

DETAILED DESCRIPTION

The following detailed description is merely illustrative and is notintended to limit embodiments and/or application or uses of embodiments.Furthermore, there is no intention to be bound by any expressed orimplied information presented in the preceding Background or Summarysections, or in the Detailed Description section.

The advantages and contribution of this disclosure include 1) mixedconfidentiality policies, 2) researchers having access to real-time logsof analyses (and not only to changes to an analysis plan), 3) blockchainlogging of the analytical steps via connection of analytical software toa blockchain contract, 4) any methods or algorithms to assess thestatistical power of the underlying result by analysis of steps on theblockchain (for example, automatic correction or reliability rating formultiple analyses) and/or 5) any integrated algorithms or blockchaincontracts that perform functions other than a) a public record of datatransactions and b) refunds based on detection of a violation of dataprovenance.

One or more embodiments are now described with reference to thedrawings, wherein like referenced numerals are used to refer to likeelements throughout. In the following description, for purposes ofexplanation, numerous specific details are set forth in order to providea more thorough understanding of the one or more embodiments. It isevident, however, in various cases, that the one or more embodiments canbe practiced without these specific details.

It is to be understood that although this disclosure includes a detaileddescription on cloud computing, implementation of the teachings recitedherein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported, providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure that includes anetwork of interconnected nodes.

Currently, problems exist because there are limited platforms that allowfor sharing information about scientific research and showingtransparent data collection and analysis steps. As a result, variouscontributors to research and/or publications may not receive accurateand/or full recognition for work performed. Further, platforms that doexist, lack the requisite controls and mechanisms to allow fortrustworthy data, as there are few options for ensuring that data willbe resistant to modification.

In various embodiments disclosed herein, solutions address the aboveproblems. For example, in one or more embodiments, provided is ablockchain system that integrates the trustworthiness of the blockchainconcept with open scientific research by generating a blockchain of theexperiments formed, data collected, analyses performed, and/or resultsachieved. Integrating the scientific process with the blockchain processcan improve the trustworthiness and/or reproducibility of the dataand/or results due to the inherently modification resistant propertiesof the blockchain. The blockchain can also be used to analyze thereliability and provenance of the data. The blockchain system can form ablockchain representing a research project, wherein the blockchaincomprises a first block of research data and a second block of analysisdata representing a log of an analysis performed on the research data.Summary blocks and correction blocks can also be added to the blockchainrepresenting the post analysis of the research results. Subsequentblocks can be linked to the preceding blocks using information in blockheaders that can also serve to determine whether modifications to theblocks have been performed, while also preserving the confidentialityinterests in the research data.

In an embodiment, this disclosure can also provide a way for scientistsand other researchers to conduct experiments and/or otherwise collectresearch data, perform analyses on the data, arrive at conclusions,perform corrections, and/or track and log their work in order for otherresearchers and scientists to perform peer reviews, try to reproduceresults, and/or generally consider the relevance and importance of theresearch without worrying whether the data or results had beenmanipulated by the original researchers or at any other step during theprocess. The blockchain system can be integrated into a cloud system andtrack data that is uploaded to public databases in some embodiments. Insome embodiments, the blockchain system can also be integrated ontoresearcher consoles and other applications that perform data collectionand analysis in order to obtain a real-time update of analyses beingperformed on the data. In an embodiment, the blockchain system can alsofacilitate working with non-public research data. Instead of using datafrom public databases, the data can be retrieved from non-publicdatabases and encrypted. The blockchain system can form blockchains fromthe data and analysis information that is encrypted.

Turning now to FIG. 1, illustrated is a high-level block diagram 100 ofan example, non-limiting blockchain system 102 in accordance with one ormore embodiments described herein. In FIG. 1, the blockchain system 102can include a processor 104, a data collection component 106, ananalysis component 108, an inspection component 110, and a correctioncomponent 112. In various embodiments, one or more of the processor 104,a data collection component 106, an analysis component 108, aninspection component 110, and a correction component 112 can beelectrically and/or communicatively coupled to one another to performone or more functions of the blockchain system 102. The blockchainsystem 102 can receive data 114 from scientific experiments, andgenerate papers 116 or processed information ready for publishing.

In some embodiments, the blockchain system 102 can be a cloud basedsystem that enables the formation of a blockchain of various steps inthe experimental/scientific research process. In other embodiments,blockchain system 102 can be based on a network or device that isperforming the data collection and analysis or is communicably coupledto the system executing the program. In an embodiment, the blockchainsystem 102 can include a processor 104 that executes computer executablecomponents stored in the memory. The components can include a datacollection component 106 that can create a master data block (e.g., datablock 206) from a data entry blockchain. The data entry blockchain canbe based on data 114 received from data collection steps in a scientificexperiment or from a public ledger (e.g., see FIG. 2). The data entryblockchain can comprise a group of data entry blocks (e.g., data blocks402 and/or 404) that are linked to each other. Blocks are linked whenhashes of previous blocks are included in the headers of subsequentblocks. Since each block can have a unique hash, a linked hash in theheader is a reference back to a specific block, thus a blockchain ofblocks. The master data block can comprise a first header and/or datafrom the data entry blocks. The header can further comprises a firsttime stamp representing when the data was collected or the master datablock formed and/or uploaded to a public ledger. The header can alsoinclude an identifier that identifies a source of the data, and a firsthash based on the data. The identifier can be a serial number associatedwith a research group or scientist, or can be associated with aapparatus that collects data (e.g., measurement device, etc).

The analysis component 108 can generate an analysis block (e.g.,analysis blocks 502 or 504) that can comprise data representing a log ofan analysis performed on the data and/or a second header that comprisesa second time stamp (e.g., when the analysis block was formed), a URLlink to the master data block, and/or a second hash based on the log ofthe analysis, wherein the analysis block and/or the master data blockcomprise a blockchain (e.g., linked blocks). The log of an analysis canbe based on a console output of a researcher tracking the calculationsand other modeling performed by the researchers. The log can includeboth the operations and algorithms performed on the data, and theresults of the processing.

The inspection component 110 can create a summary block or inspectioncomponent (e.g., inspection component 602) comprising a summary of thedata, a summary of the analysis and a result of the analysis, and/or athird header comprising a link to the analysis block. The components canalso include a correction component 112 that rates a reliability of theresult of the analysis based on the summary of the analysis and/or thelog of the analysis, wherein the reliability is associated with a numberof attempts to achieve the result of the analysis. For instance, ananalysis sequence with many steps and/or attempts to match data to amodel might have a lower reliability rating than an analysis sequencewith fewer steps.

The blockchain system 102 and/or the components of the blockchain system102 can employ hardware and/or software to solve problems that arehighly technical in nature (e.g., related to bioinformatics,authentication, compression, big data analysis etc.), that are notabstract and that cannot be performed as a set of mental acts by ahuman. The blockchain system 102 and/or components of the system can beemployed to solve new problems that arise through advancements intechnology (e.g., provenance of data, reliability/integrity ofresearch), computer networks, the Internet and/or the like.

A processor 104 can be associated with at least one of a centralprocessor, a graphical processor, etc. In various embodiments, theprocessor 104 can be or include hardware, software (e.g., a set ofthreads, a set of processes, software in execution, etc.) or acombination of hardware and/or software that performs a computing taskfor machine learning (e.g., a machine learning computing task associatedwith received data). For example, the processor 104 can execute dataanalysis threads that cannot be performed by a human (e.g., are greaterthan the capability of a single human mind). For example, the amount ofdata processed, the speed of processing of the data and/or the datatypes processed by processor 104 over a certain period of time can berespectively greater, faster and different than the amount, speed anddata type that can be processed by a single human mind over the sameperiod of time. For example, data processed by processor 104 can be rawdata (e.g., raw audio data, raw video data, raw textual data, rawnumerical data, etc.) and/or compressed data (e.g., compressed audiodata, compressed video data, compressed textual data, compressednumerical data, etc.) captured by one or more sensors and/or one or morecomputing devices. Moreover, processor 104 can be fully operationaltowards performing one or more other functions (e.g., fully powered on,fully executed, etc.) while also processing the above-referenced dataanalysis data and runtime environment data.

Turning now to FIG. 2, illustrated is another high-level block diagram200 of the example, non-limiting blockchain system 102 in accordancewith one or more embodiments described herein. Repetitive description oflike elements employed in other embodiments described herein is omittedfor sake of brevity.

In an embodiment, the data collection component 106 can receive theresearch and/or experimental data from a database 202. The database 202can be a public ledger or non-public database associated with one ormore of the research groups. The database can store the data in blockform, such as depicted by blocks 204, 206, and/or 208 with headersand/or data portions. In a embodiments, the database 202 can store thedata in raw form, separated by experiments performed, researchers whocollected the data, subjects, participants, or other distinguishingelements.

Turning now to FIG. 3 illustrated a flow diagram of an example,non-limiting computer-implemented method 300 of integrating blockchainfunctionality with open scientific research in accordance with one ormore embodiments described herein. Repetitive description of likeelements employed in other embodiments described herein is omitted forsake of brevity.

In an embodiment, the flow diagram can begin at 302, where theexperiment or project identifier (ID) can be retrieved and/or otherwiseestablished. The project ID can be used in the headers of the blocksforming the blockchain as a way to identify the blockchain and associateit with the experiment or research project.

The project ID can be attached to the data that is collected at 304. Thedata collected at 304 can be associated with the data from the researchproject or experiment, and can include data that was collected from aproject or experiment that was formerly conducted, or data that iscollected as the project or experiment is proceeding. The data caninclude data collected from one or more scientific instruments, frompeople providing feedback (e.g., interviews, observational data, etc) orother data retrieved via online assessments, data harvesting, big datacollection, and etc.

In an embodiment, the data collected at 304 can be separated intodatasets from individuals, groups of researchers, or differentexperiments or the same experiments conducted at different times. In anembodiment, the blockchain system can generate a block comprising thedata, and in other embodiments, the blockchain system can generateseparate blocks, wherein separate datasets are formed into a block. Theblocks can comprise a data portion and/or a header, with the headercomprising the project ID and other information that can be used to linkthe blocks together. In an embodiment, the blocks can be formed into ablockchain to preserve the data and make it resistant to modification.The blocks are formed into a blockchain by including a hash of theprevious block in the header of a subsequent block. The chain of hashesfrom earlier blocks to later blocks results in the blockchain, and theyare resistant to modification due to the nature of the hash. Since ahash is a unique number based on the data inside each block, if there isany change in data, a new hash results. The new hash would cause adiscontinuity in the blockchain, eliminating the blockchain.

In an embodiment, the data can be collected from, or the blockchainstored on, a public or non-public database. The links that link theblocks in the blockchain can be a uniform resource locator (URL) orother database link. In some embodiments, the link can be the hash ofthe previous block. If a first block is hashed, the hash can uniquelyidentify that block, and a subsequent block can be linked to the firstblock by including the hash of the first block in the header of thesecond block.

In an embodiment, in response to the data being collected at 304 (e.g.,by data collection component 106), the data can be written into a block,or, in other embodiments, a block is formed based on the data. Asanother or subsequent block is created, then it can be linked to thefirst/previous block. A timestamp can be included in the header as wellto identify the order in which the blocks were received. In cases whereblocks are collected at the same time and therefore have the sametimestamp, the order in which the blocks are written to an onlinedatabase and/or server (e.g., database 202) or collected can establishthe order the blocks are located within the blockchain.

At 306, the analysis component 108 can perform processing. By way ofexample, but not limitation, processing can include adding blocks to theblockchain representing initial data reduction not related to the formalanalysis of fitting data to the one or more models. Data reduction andother processing steps can be included in processing 306. These stepscan include the generation of the has by the processor 104 that performsa hashing function that generates a unique number based on the data inthe blocks. In other embodiments, the processing steps can include datareduction, manipulation, and other processing steps performed on thedata to organize the raw data. The processing steps can also becalculations and other algorithms performed on the data to try toconform the data to one or more hypothesized models. The processing canalso include other data modeling functions performed on the datacollected at 304.

In an embodiment, the processing steps can be determined based on one ormore analysis logs collected from the research group, a public ornon-public database, or the console application that performed theanalysis. In an embodiment, the blockchain system can generate ananalysis block comprising the steps, and a header with information usedto link the analysis block to the blockchain formed at 304.

At 308, the analysis component 108 can generate a series of analysisblocks, where one or more analysis blocks is associated with one or moreof the calculations, and other processing functions. In this way, theprocessing steps can be preserved on the blockchain for inspection andcorrection at a later time. In an embodiment, one or more of theanalysis blocks can correspond to separate data blocks, or include oneor more analyses performed on a data set associated with the data block.

At 310, the inspection component 110 can confirm the participants inboth the processing/analysis steps at 306 and/or 308, as well as duringthe data collection at 304. Confirming the participants can include, butis not limited to, inspecting the headers of one or more of the datablocks to determine the source of the data, and which researcher,research group, or other participant accessed and/or modified the datavia the one or more analysis steps.

It is to be appreciated that at one or more of these preceding andsubsequent steps, the blockchain system can update the blockchain on thepublic or non-public ledger/database in real-time or at predefinedintervals (e.g., every x minutes, or when a block is added to theblockchain) so that other entities can access the blockchain to inspectthe blockchain, and see the research process.

At 312, the inspection process is performed where the inspectioncomponent 110 can summarize the data and analyses steps 306, 308performed previously, and determine a result of the research project orother conclusion. In an embodiment, the inspection component can includejust the headers of the data blocks and the analysis blocks to link backto. In an additional embodiment, the inspection component can have aheader that includes a hash that is the hash of the last analysis block.

The inspection step 312 can also take information and/or data about theresearch project or experiment that is outside the blockchain, andcompare it to the results and data reported in the blockchain to confirmthe veracity and reliability of the outside information.

In another embodiment, the blockchain system 102 can include one or moreprotocols whereby the inspection component is not added to theblockchain or otherwise registered until it is confirmed that theinspection component incorporates the outputs of the analyst blocks andtheir hashes. Including the hashes ensures that not only the identify ofwhich block in the blockchain results in the outcome, but that you canalso verify the reliability of the block and the outcome with the hash.

At 314, the correction component 112 can perform a correction wherebythe relative reliability or importance of the research and/orexperimental conclusions can be determined. For instance, if relativelyfew analyses steps or modifications of the processing algorithms arerequired to achieve the hypothesized result, then the experiment orresearch conclusion can have a more highly weighted importance than ifmany modifications are performed. The blockchain system can determinehow many modifications are performed by determining which of theanalysis blocks resulted in the outcome—if an early analysis blockresulted in the outcome, than the result can be weighted higher than ifa later analysis block resulted in the outcome. The blockchain systemcan also determine the weighting based on the types of modificationsreported in the analysis blocks.

At 316, the correction component 112 can assist in the publication ofthe research project. The blockchain system can access the datablock(s), analysis block(s), inspection component(s) (which comprise thesummary and outcome), and the correction block(s) to gather the data,and format it for publishing and otherwise make the information easilyaccessible to one or more of the researchers when writing the article.

At 318, the inspection component 110 can finalize, and store theblockchain and other information on one or more public ledgers ordatabases, or non-public databases for peer review which can take placeat 320.

Turning now to FIG. 4, illustrated is block diagram 400 of an example,non-limiting set of data blocks that forms a data blockchain fromseparate sets of data in accordance with one or more embodimentsdescribed herein. Repetitive description of like elements employed inother embodiments described herein is omitted for sake of brevity.

The blockchain system (e.g., blockchain system 102), when collectingdata (as described in step 304 above) can gather data from separate datasets such as data block A 402 and data block B 404 and form a largerdata block 406 that comprises the data blocks 402 and 404.

In an embodiment, the data collected, that is used to generate datablocks 402 and 404, can be associated with the data from the researchproject or experiment, and can include data that was collected from aproject or experiment that was formerly conducted, or data that iscollected as the project or experiment is proceeding. As an example,data block A 402 can be associated with data received from a firstexperiment, and data block B 404 can be associated with data receivedfrom a second experiment, or a second run of the first experiment. Thedata can include data collected from one or more scientific instruments,from people providing feedback (e.g., interviews, observational data,etc) or other data retrieved via online assessments, data harvesting,big data collection, and etc.

In an embodiment, the data collected can be separated into datasetse.g., data block A 402 and data block B 404 from individuals, groups ofresearchers, or different experiments or the same experiments conductedat different times. In an embodiment, the blockchain system can generatea block comprising the data, and in other embodiments, the blockchainsystem can generate separate blocks, wherein one or more of the separatedatasets is formed into a block. The blocks can comprise a data portionand a header, with the header comprising the project ID and otherinformation that can be used to link the blocks together. In anembodiment, one or more of the blocks can be formed into a blockchain topreserve the data and make it resistant to modification.

In some embodiments, the data in one or more of data blocks A and B 402and 404 can be encrypted. In some embodiments, some or all of the datain a block can be encrypted, or in other embodiments, to protect thesource of the data, the header can be encrypted while the data portionof the block is unencrypted.

The data blocks in the blockchain (e.g., data blocks 402 and 404) caninclude hashes in the headers of the preceding datablocks. The hashescan link one or more block to each other and also provide a way todetermine if any data modifications have been performed. The blockchainsystem can compare the hashes, and if the hashes do not match eachother, it can indicate that a modification or alteration to the datablock with the mismatched hash has been performed.

Turning now to FIG. 5, illustrated is another block diagram 500 of anexample, blockchain in accordance with one or more embodiments describedherein. Repetitive description of like elements employed in otherembodiments described herein is omitted for sake of brevity.

The blockchain system 102 can join analysis blocks A and B (504 and 502respectively) to the data blockchain 406. The analysis blocks 502 and504 can be joined as various processing steps and/or computationalgorithms are performed on the data collected in data blocks 402 and404. In other embodiments, the analysis blocks 502 and 504 can be formedafter the experiment is conducted based on the logs of the researchers,scientists, and/or other personnel involved in the data analyses.

The logs can include notes written by the researchers documenting thetypes of data analyses performed and the results of the analyses andtranscribed or otherwise transformed into an electronic form andcollected by blockchain system. In other embodiments, the logs can beobtained from a researcher console, or other application that performedduring the analysis steps.

One or more of the analysis blocks 502 and 504 can correspond todifferent sets of analyses performed on the data. For instance, if afirst calculation is performed and a result is obtained, analysis block504 can document and record the analysis. Then, separately, or based onthe result of the first calculation, if a second calculation and secondresult is obtained, the analysis block 502 can document and record theanalysis and outcome of the second calculation. In other embodiments,one or more of the analysis blocks 502 and 504 can document all or partof the analyses performed on data blocks 402 and 404 respectively. In anembodiment the data or the headers of the analysis blocks 502 and 504can be encrypted.

One or more of the analysis blocks 502 and 504 can have headers thatcomprise information relating to the source of the log file or identityof the researcher or research group, a time stamp, and a hash or link ofor to the previous block. For instance, analysis block 504 can include alink to the previous data block, and block 502 can include a link toblock 504.

In an embodiment, the blockchain can be linear, where the data iscollected first, and then the analysis blocks are added linearly to theblockchain based on the order in which they are added to a database orledger. In other embodiments, the blockchain can bifurcate as processingis performed and documented on datasets as they are gathered before oneor more of the data sets are gathered. In such an embodiment, as anexample, analysis block 502 can link directly to data block 402, andanalysis block 504 can link directly to data block 404.

Turning now to FIG. 6, illustrated is another block diagram 600 of anexample, non-limiting open research blockchain in accordance with one ormore embodiments described herein. Repetitive description of likeelements employed in other embodiments described herein is omitted forsake of brevity.

Diagram 600 depicts an example blockchain created by the blockchainsystem comprising an example set of blocks, including data blocks 402and 404, analysis blocks 504 and 502, inspection component 602, andcorrection block 604.

The data blocks 402 and 404 can comprise the research/experimental datacollected by one or more of the experiments, instruments, interviews,and other collection methods. The data in data blocks 402 and 404 cancorrespond to data from separate experiments, different runs, differentresearchers and/or participants and etc. The analysis blocks 502 and 504can document the analyses performed on the data in data blocks 402 and404, and can comprise information related to modifications of scriptsperformed on the data blocks over time. For instance, if a dataprocessing/modeling script is performed on either data in data block 402or 404, the result of the script, and information about the script canbe stored, logged, or otherwise documented in analysis block 504. If thescript is modified or otherwise altered in anyway, or the same script isperformed on a different set of data, the results and information aboutthe script can be documented in analysis block 502.

Inspection component 602 can comprise a summary of the analysesperformed, results obtained, and other conclusions obtained in theprevious blocks in the blockchain. In an embodiment, the inspectioncomponent can also comprise the headers of the data blocks and theanalysis blocks to link back to. In an additional embodiment, theinspection component can have a header that includes a hash that is thehash of the last analysis block.

In another embodiment, the blockchain system can include one or moreprotocols whereby the inspection component 602 is not added to theblockchain or otherwise registered until it is confirmed that theinspection component incorporates the outputs of the analyst blocks andtheir hashes. Including the hashes ensures that not only the identify ofwhich block in the blockchain results in the outcome, but that you canalso verify the reliability of the block and the outcome with the hash.As an example, the inspection component can comprise the console outputsof the researchers which can be linked back to the analysis blocks 502and 504. The hashes of the analysis blocks can be compared to the hashesof the console output to verify that no other modifications oralterations to the results and logs have been made.

The correction block 604 can comprise a weighting or relative importanceranking of the results obtained during the analysis blocks andinspection component. For instance, if relatively few analyses steps ormodifications of the data processing algorithms are required to achievethe hypothesized result, then the experiment or research conclusion canhave a more highly weighted importance than if many modifications areperformed. The blockchain system can determine how many modificationsare performed by determining which of the analysis blocks resulted inthe outcome—if an early analysis block resulted in the outcome, than theresult can be weighted higher than if a later analysis block resulted inthe outcome. The blockchain system can also determine the weightingbased on the types of modifications reported in the analysis blocks 502and 504.

Turning now to FIG. 7, illustrated is another block diagram 700 of anexample, non-limiting system of headers and data portions of a datablockchain in accordance with one or more embodiments described herein.Repetitive description of like elements employed in other embodimentsdescribed herein is omitted for sake of brevity.

Diagram 700 depicts the structure of data blocks 402 and 404. It is tobe appreciated that the structure of blocks 402 and 404 can apply toother blocks in the blockchain (e.g., analysis blocks 502 and 504,inspection component 602 and correction block 604).

In an embodiment, one or more of blocks 402 and 404 can include a header702 and 716 respectively, as well as a data portion 710 and 722respectively. The headers 702 and 716 can include informationidentifying the researcher, research group, experiment or project(identifiers 706 and 720). The data blocks 402 and 404 can also includea timestamp 704 and 718 that identify the time that the data blocks wereformed on the server, or the sets of data in data portions 710 and 716were received by the server or collected.

Data block 402 can also include a hash A 714 that is a number of apredefined length that is received in response to a hash functionperforming a hash of the data in data portion 710 or in an embodiment,of some or all the data in the data block 402, including the header 702.The hash is a unique number based on the content of the data, and evensmall modifications to the data can result in hash numbers that aredistinctly different.

The hash A 714 of data block 402 can be included in the header ofsubsequent block 404. By linking the hash A 714 in 404, the blockchainis formed, and any modifications of data would result in the hashes notmatching, breaking the blockchain.

In various embodiments, the headers 702 and 716 may also include URLslinking to data in one or more public or non-public databases/ledgers.

In an embodiment, the headers 702 and 716 or the data portions 710 and722 can be encrypted to protect sensitive information. The researcher IDcan be linked to a public key which can facilitate decryption of theencrypted data and/or header. In some embodiments, the data can beencrypted while the headers, with the hashes and identifiers are notencrypted. This can allow the researcher to make the data non-public,while enabling peer reviewers to replicate the results using theencrypted data.

Turning now to FIG. 8, illustrated is a flow diagram 800 of an example,non-limiting computer-implemented method that forms a blockchain basedon research data and analysis in accordance with one or more embodimentsdescribed herein.

The method can begin at 802, where the method includes receiving, by adevice operatively coupled to a processor, a first file havingexperimental data (e.g., by data collection component 106). The firstfile can be received from a public database or ledger or from anon-public database. The file can include one or more data sets thatcorrespond to respective participants or experiments performed.

The method can continue at 804, where the method includes generating, bythe device, a first block from the first file, wherein the first blockcomprises a first header and the experimental data, wherein the headerfurther comprises a first time stamp, an identifier that identifies asource of the experimental data, and a first hash based on theexperimental data (e.g., by data collection component 106). The firstblock can be comprised of many blocks corresponding to one or more ofthe separate data sets. One or more of the blocks can have respectiveheaders with respective time stamps, identifiers, and hashes. The hashesof the data portions of a preceding block can be included in the headerof the subsequent block to provide a link in the blockchain, and to alsoprovide reliability and tamper resistance to the blockchain.

The method can continue at 806, where the method includes receiving, bythe device, a second file that comprises a log of an analysis performedon the experimental data (e.g., by analysis component 108). The log ofthe analysis can include some or all of the data analyses and scriptsrelating to the processing as well as the results of the data analyses.

The method continues at 808, where generating, by the device, a secondblock based on the second file, wherein the second block comprises thelog of the analysis and a second header that comprises a second timestamp, a link to the first block, and a second hash based on the log ofthe analysis (e.g., by analysis component 108).

Turning now to FIG. 9, illustrated a flow diagram 900 of an example,non-limiting computer-implemented method that forms a blockchain basedon research data and analysis in accordance with one or more embodimentsdescribed herein. Repetitive description of like elements employed inother embodiments described herein is omitted for sake of brevity

The method can begin at 902, where the method includes forming, by adevice operatively coupled to a processor, a blockchain representing aresearch project, wherein the blockchain comprises a first block ofresearch data, and a second block of analysis data representing a log ofan analysis performed on the research data (e.g., by data collectioncomponent 106 and analysis component 108).

The method can continue at 904, where the method includes forming, bythe device, a summary block comprising a summary of the research dataand summary of the analysis data (e.g., by inspection component 110).

The method can continue at 906, where the method includes appending, bythe device, the summary block to the blockchain (e.g., by inspectioncomponent 110).

For simplicity of explanation, the computer-implemented methodologiesare depicted and described as a series of acts. It is to be understoodand appreciated that the subject innovation is not limited by the actsillustrated and/or by the order of acts, for example acts can occur invarious orders and/or concurrently, and with other acts not presentedand described herein. Furthermore, not all illustrated acts can berequired to implement the computer-implemented methodologies inaccordance with the disclosed subject matter. In addition, those skilledin the art will understand and appreciate that the computer-implementedmethodologies could alternatively be represented as a series ofinterrelated states via a state diagram or events. Additionally, itshould be further appreciated that the computer-implementedmethodologies disclosed hereinafter and throughout this specificationare capable of being stored on an article of manufacture to facilitatetransporting and transferring such computer-implemented methodologies tocomputers. The term article of manufacture, as used herein, is intendedto encompass a computer program accessible from any computer-readabledevice or storage media.

Moreover, because configuration of data packet(s) and/or communicationbetween processors and/or an assignment component is established from acombination of electrical and mechanical components and circuitry, ahuman is unable to replicate or perform the subject data packetconfiguration and/or the subject communication between processors and/oran assignment component. For example, a human is unable to generate datafor transmission over a wired network and/or a wireless network betweenprocessors and/or an assignment component, etc. Moreover, a human isunable to packetize data that can include a sequence of bitscorresponding to information generated during a machine learning process(e.g., a blockchain formation process), transmit data that can include asequence of bits corresponding to information generated during a machinelearning process (e.g., a corresponding to information generated duringa machine learning process (e.g., a blockchain formation process), etc.

In order to provide a context for the various aspects of the disclosedsubject matter, FIG. 10 as well as the following discussion are intendedto provide a general description of a suitable environment in which thevarious aspects of the disclosed subject matter can be implemented. FIG.10 illustrates a block diagram of an example, non-limiting operatingenvironment in which one or more embodiments described herein can befacilitated. Repetitive description of like elements employed in otherembodiments described herein is omitted for sake of brevity. Withreference to FIG. 10, a suitable operating environment 1000 forimplementing various aspects of this disclosure can also include acomputer 1012. The computer 1012 can also include a processor 1014, asystem memory 1016, and a system bus 1018. The system bus 1018 couplessystem components including, but not limited to, the system memory 1016to the processor 1014. The processor 1014 can be any of variousavailable processors. Dual microprocessors and other multiprocessorarchitectures also can be employed as the processor 1014. The system bus1018 can be any of several types of bus structure(s) including thememory bus or memory controller, a peripheral bus or external bus,and/or a local bus using any variety of available bus architecturesincluding, but not limited to, Industrial Standard Architecture (ISA),Micro-Channel Architecture (MSA), Extended ISA (EISA), Intelligent DriveElectronics (IDE), VESA Local Bus (VLB), Peripheral ComponentInterconnect (PCI), Card Bus, Universal Serial Bus (USB), AdvancedGraphics Port (AGP), Firewire (IEEE 1394), and Small Computer SystemsInterface (SCSI). The system memory 1016 can also include volatilememory 1020 and nonvolatile memory 1022. The basic input/output system(BIOS), containing the basic routines to transfer information betweenelements within the computer 1012, such as during start-up, is stored innonvolatile memory 1022. By way of illustration, and not limitation,nonvolatile memory 1022 can include read only memory (ROM), programmableROM (PROM), electrically programmable ROM (EPROM), electrically erasableprogrammable ROM (EEPROM), flash memory, or nonvolatile random accessmemory (RAM) (e.g., ferroelectric RAM (FeRAM). Volatile memory 1020 canalso include random access memory (RAM), which acts as external cachememory. By way of illustration and not limitation, RAM is available inmany forms such as static RAM (SRAM), dynamic RAM (DRAM), synchronousDRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM(ESDRAM), Synchlink DRAM (SLDRAM), direct Rambus RAM (DRRAM), directRambus dynamic RAM (DRDRAM), and Rambus dynamic RAM.

Computer 1012 can also include removable/non-removable,volatile/nonvolatile computer storage media. FIG. 10 illustrates, forexample, a disk storage 1024. Disk storage 1024 can also include, but isnot limited to, devices like a magnetic disk drive, floppy disk drive,tape drive, Jaz drive, Zip drive, LS-100 drive, flash memory card, ormemory stick. The disk storage 1024 also can include storage mediaseparately or in combination with other storage media including, but notlimited to, an optical disk drive such as a compact disk ROM device(CD-ROM), CD recordable drive (CD-R Drive), CD rewritable drive (CD-RWDrive) or a digital versatile disk ROM drive (DVD-ROM). To facilitateconnection of the disk storage 1024 to the system bus 1018, a removableor non-removable interface is typically used, such as interface 1026.FIG. 10 also depicts software that acts as an intermediary between usersand the basic computer resources described in the suitable operatingenvironment 1000. Such software can also include, for example, anoperating system 1028. Operating system 1028, which can be stored ondisk storage 1024, acts to control and allocate resources of thecomputer 1012. System applications 1030 take advantage of the managementof resources by operating system 1028 through program modules 1032 andprogram data 1034, e.g., stored either in system memory 1016 or on diskstorage 1024. It is to be appreciated that this disclosure can beimplemented with various operating systems or combinations of operatingsystems. An entity enters commands or information into the computer 1012through input device(s) 1036. Input devices 1036 include, but are notlimited to, a pointing device such as a mouse, trackball, stylus, touchpad, keyboard, microphone, joystick, game pad, satellite dish, scanner,TV tuner card, digital camera, digital video camera, web camera, and thelike. These and other input devices connect to the processor 1014through the system bus 1018 via interface port(s) 1038. Interfaceport(s) 1038 include, for example, a serial port, a parallel port, agame port, and a universal serial bus (USB). Output device(s) 1040 usesome of the same type of ports as input device(s) 1036. Thus, forexample, a USB port can be used to provide input to computer 1012, andto output information from computer 1012 to an output device 1040.Output adapter 1042 is provided to illustrate that there are some outputdevices 1040 like monitors, speakers, and printers, among other outputdevices 1040, which require special adapters. The output adapters 1042include, by way of illustration and not limitation, video and soundcards that provide a means of connection between the output device 1040and the system bus 1018. It should be noted that other devices and/orsystems of devices provide both input and output capabilities such asremote computer(s) 1044.

Computer 1012 can operate in a networked environment using logicalconnections to one or more remote computers, such as remote computer(s)1044. The remote computer(s) 1044 can be a computer, a server, a router,a network PC, a workstation, a microprocessor based appliance, a peerdevice or other common network node and the like, and typically can alsoinclude many or all of the elements described relative to computer 1012.For purposes of brevity, only a memory storage device 1046 isillustrated with remote computer(s) 1044. Remote computer(s) 1044 islogically connected to computer 1012 through a network interface 1048and then physically connected via communication connection 1050. Networkinterface 1048 encompasses wire and/or wireless communication networkssuch as local-area networks (LAN), wide-area networks (WAN), cellularnetworks, etc. LAN technologies include Fiber Distributed Data Interface(FDDI), Copper Distributed Data Interface (CDDI), Ethernet, Token Ringand the like. WAN technologies include, but are not limited to,point-to-point links, circuit switching networks like IntegratedServices Digital Networks (ISDN) and variations thereon, packetswitching networks, and Digital Subscriber Lines (DSL). Communicationconnection(s) 1050 refers to the hardware/software employed to connectthe network interface 1048 to the system bus 1018. While communicationconnection 1050 is shown for illustrative clarity inside computer 1012,it can also be external to computer 1012. The hardware/software forconnection to the network interface 1048 can also include, for exemplarypurposes only, internal and external technologies such as, modemsincluding regular telephone grade modems, cable modems and DSL modems,ISDN adapters, and Ethernet cards.

Referring now to FIG. 11, an illustrative cloud computing environment1150 is depicted. As shown, cloud computing environment 1150 includesone or more cloud computing nodes 1110 with which local computingdevices used by cloud consumers, such as, for example, personal digitalassistant (PDA) or cellular telephone 1654A, desktop computer 1154B,laptop computer 1154C, and/or automobile computer system 1154N maycommunicate. Nodes 1110 may communicate with one another. They may begrouped (not shown) physically or virtually, in one or more networks,such as Private, Community, Public, or Hybrid clouds as describedhereinabove, or a combination thereof. This allows cloud computingenvironment 1150 to offer infrastructure, platforms and/or software asservices for which a cloud consumer does not need to maintain resourceson a local computing device. It is understood that the types ofcomputing devices 1154A-N shown in FIG. 11 are intended to beillustrative only and that computing nodes 1110 and cloud computingenvironment 1150 can communicate with any type of computerized deviceover any type of network and/or network addressable connection (e.g.,using a web browser).

Referring now to FIG. 12, a set of functional abstraction layersprovided by cloud computing environment 1150 (FIG. 11) is shown. Itshould be understood in advance that the components, layers, andfunctions shown in FIG. 12 are intended to be illustrative only andembodiments of the invention are not limited thereto. As depicted, thefollowing layers and corresponding functions are provided:

Hardware and software layer 1260 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 1261;RISC (Reduced Instruction Set Computer) architecture based servers 1262;servers 1263; blade servers 1264; storage devices 1265; and networks andnetworking components 1266. In some embodiments, software componentsinclude network application server software 1267 and database software1268.

Virtualization layer 1270 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers1271; virtual storage 1272; virtual networks 1273, including virtualprivate networks; virtual applications and operating systems 1274; andvirtual clients 1275.

In one example, management layer 1280 may provide the functionsdescribed below. Resource provisioning 1281 provides dynamic procurementof computing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 1282provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may include applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 1283 provides access to the cloud computing environment forconsumers and system administrators. Service level management 1284provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 1285 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 1290 provides examples of functionality for which thecloud computing environment may be utilized. Non-limiting examples ofworkloads and functions which may be provided from this layer include:mapping and navigation 1291; software development and lifecyclemanagement 1292; virtual classroom education delivery 1293; dataanalytics processing 1294; transaction processing 1295; and transactionmodel software 1296.

The present invention may be a system, a method, an apparatus and/or acomputer program product at any possible technical detail level ofintegration. The computer program product can include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention. The computer readable storage medium can be atangible device that can retain and store instructions for use by aninstruction execution device. The computer readable storage medium canbe, for example, but is not limited to, an electronic storage device, amagnetic storage device, an optical storage device, an electromagneticstorage device, a semiconductor storage device, or any suitablecombination of the foregoing. A non-exhaustive list of more specificexamples of the computer readable storage medium can also include thefollowing: a portable computer diskette, a hard disk, a random accessmemory (RAM), a read-only memory (ROM), an erasable programmableread-only memory (EPROM or Flash memory), a static random access memory(SRAM), a portable compact disc read-only memory (CD-ROM), a digitalversatile disk (DVD), a memory stick, a floppy disk, a mechanicallyencoded device such as punch-cards or raised structures in a groovehaving instructions recorded thereon, and any suitable combination ofthe foregoing. A computer readable storage medium, as used herein, isnot to be construed as being transitory signals per se, such as radiowaves or other freely propagating electromagnetic waves, electromagneticwaves propagating through a waveguide or other transmission media (e.g.,light pulses passing through a fiber-optic cable), or electrical signalstransmitted through a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network can comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device. Computer readable programinstructions for carrying out operations of the present invention can beassembler instructions, instruction-set-architecture (ISA) instructions,machine instructions, machine dependent instructions, microcode,firmware instructions, state-setting data, configuration data forintegrated circuitry, or either source code or object code written inany combination of one or more programming languages, including anobject oriented programming language such as Smalltalk, C++, or thelike, and procedural programming languages, such as the “C” programminglanguage or similar programming languages. The computer readable programinstructions can execute entirely on the user's computer, partly on theuser's computer, as a stand-alone software package, partly on the user'scomputer and partly on a remote computer or entirely on the remotecomputer or server. In the latter scenario, the remote computer can beconnected to the user's computer through any type of network, includinga local area network (LAN) or a wide area network (WAN), or theconnection can be made to an external computer (for example, through theInternet using an Internet Service Provider). In some embodiments,electronic circuitry including, for example, programmable logiccircuitry, field-programmable gate arrays (FPGA), or programmable logicarrays (PLA) can execute the computer readable program instructions byutilizing state information of the computer readable programinstructions to personalize the electronic circuitry, in order toperform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions. These computer readable programinstructions can be provided to a processor of a general purposecomputer, special purpose computer, or other programmable data analysesapparatus to produce a machine, such that the instructions, whichexecute via the processor of the computer or other programmable dataprocessing apparatus, create means for implementing the functions/actsspecified in the flowchart and/or block diagram block or blocks. Thesecomputer readable program instructions can also be stored in a computerreadable storage medium that can direct a computer, a programmable dataprocessing apparatus, and/or other devices to function in a particularmanner, such that the computer readable storage medium havinginstructions stored therein comprises an article of manufactureincluding instructions which implement aspects of the function/actspecified in the flowchart and/or block diagram block or blocks. Thecomputer readable program instructions can also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational acts to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams can represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks can occur out of theorder noted in the Figures. For example, two blocks shown in successioncan, in fact, be executed substantially concurrently, or the blocks cansometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

While the subject matter has been described above in the general contextof computer-executable instructions of a computer program product thatruns on a computer and/or computers, those skilled in the art willrecognize that this disclosure also can or can be implemented incombination with other program modules. Generally, program modulesinclude routines, programs, components, data structures, etc. thatperform particular tasks and/or implement particular abstract datatypes. Moreover, those skilled in the art will appreciate that theinventive computer-implemented methods can be practiced with othercomputer system configurations, including single-processor ormultiprocessor computer systems, mini-computing devices, mainframecomputers, as well as computers, hand-held computing devices (e.g., PDA,phone), microprocessor-based or programmable consumer or industrialelectronics, and the like. The illustrated aspects can also be practicedin distributed computing environments where tasks are performed byremote processing devices that are linked through a communicationsnetwork. However, some, if not all aspects of this disclosure can bepracticed on stand-alone computers. In a distributed computingenvironment, program modules can be located in both local and remotememory storage devices.

As used in this application, the terms “component,” “system,”“platform,” “interface,” and the like, can refer to and/or can include acomputer-related entity or an entity related to an operational machinewith one or more specific functionalities. The entities disclosed hereincan be either hardware, a combination of hardware and software,software, or software in execution. For example, a component can be, butis not limited to being, a process running on a processor, a processor,an object, an executable, a thread of execution, a program, and/or acomputer. By way of illustration, both an application running on aserver and the server can be a component. One or more components canreside within a process and/or thread of execution and a component canbe localized on one computer and/or distributed between two or morecomputers. In another example, respective components can execute fromvarious computer readable media having various data structures storedthereon. The components can communicate via local and/or remoteprocesses such as in accordance with a signal having one or more datapackets (e.g., data from one component interacting with anothercomponent in a local system, distributed system, and/or across a networksuch as the Internet with other systems via the signal). As anotherexample, a component can be an apparatus with specific functionalityprovided by mechanical parts operated by electric or electroniccircuitry, which is operated by a software or firmware applicationexecuted by a processor. In such a case, the processor can be internalor external to the apparatus and can execute at least a part of thesoftware or firmware application. As yet another example, a componentcan be an apparatus that provides specific functionality throughelectronic components without mechanical parts, wherein the electroniccomponents can include a processor or other means to execute software orfirmware that confers at least in part the functionality of theelectronic components. In an aspect, a component can emulate anelectronic component via a virtual machine, e.g., within a cloudcomputing system.

In addition, the term “or” is intended to mean an inclusive “or” ratherthan an exclusive “or.” That is, unless specified otherwise, or clearfrom context, “X employs A or B” is intended to mean any of the naturalinclusive permutations. That is, if X employs A; X employs B; or Xemploys both A and B, then “X employs A or B” is satisfied under any ofthe foregoing instances. Moreover, articles “a” and “an” as used in thesubject specification and annexed drawings should generally be construedto mean “one or more” unless specified otherwise or clear from contextto be directed to a singular form. As used herein, the terms “example”and/or “exemplary” are utilized to mean serving as an example, instance,or illustration. For the avoidance of doubt, the subject matterdisclosed herein is not limited by such examples. In addition, anyaspect or design described herein as an “example” and/or “exemplary” isnot necessarily to be construed as preferred or advantageous over otheraspects or designs, nor is it meant to preclude equivalent exemplarystructures and techniques known to those of ordinary skill in the art.

As it is employed in the subject specification, the term “processor” canrefer to substantially any computing processor or device comprising, butnot limited to, single-core processors; single-processors with softwaremultithread execution capability; multi-core processors; multi-coreprocessors with software multithread execution capability; multi-coreprocessors with hardware multithread technology; parallel platforms; andparallel platforms with distributed shared memory. Additionally, aprocessor can refer to an integrated circuit, an application specificintegrated circuit (ASIC), a digital signal processor (DSP), a fieldprogrammable gate array (FPGA), a programmable logic controller (PLC), acomplex programmable logic device (CPLD), a discrete gate or transistorlogic, discrete hardware components, or any combination thereof designedto perform the functions described herein. Further, processors canexploit nano-scale architectures such as, but not limited to, molecularand quantum-dot based transistors, switches and gates, in order tooptimize space usage or enhance performance of user equipment. Aprocessor can also be implemented as a combination of computingprocessors. In this disclosure, terms such as “store,” “storage,” “datastore,” data storage,” “database,” and substantially any otherinformation storage component relevant to operation and functionality ofa component are utilized to refer to “memory components,” entitiesembodied in a “memory,” or components comprising a memory. It is to beappreciated that memory and/or memory components described herein can beeither volatile memory or nonvolatile memory, or can include bothvolatile and nonvolatile memory. By way of illustration, and notlimitation, nonvolatile memory can include read only memory (ROM),programmable ROM (PROM), electrically programmable ROM (EPROM),electrically erasable ROM (EEPROM), flash memory, or nonvolatile randomaccess memory (RAM) (e.g., ferroelectric RAM (FeRAM). Volatile memorycan include RAM, which can act as external cache memory, for example. Byway of illustration and not limitation, RAM is available in many formssuch as synchronous RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM(SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM),Synchlink DRAM (SLDRAM), direct Rambus RAM (DRRAM), direct Rambusdynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM). Additionally, thedisclosed memory components of systems or computer-implemented methodsherein are intended to include, without being limited to including,these and any other suitable types of memory.

What has been described above include mere examples of systems andcomputer-implemented methods. It is, of course, not possible to describeevery conceivable combination of components or computer-implementedmethods for purposes of describing this disclosure, but one of ordinaryskill in the art can recognize that many further combinations andpermutations of this disclosure are possible. Furthermore, to the extentthat the terms “includes,” “has,” “possesses,” and the like are used inthe detailed description, claims, appendices and drawings such terms areintended to be inclusive in a manner similar to the term “comprising” as“comprising” is interpreted when employed as a transitional word in aclaim. The descriptions of the various embodiments have been presentedfor purposes of illustration, but are not intended to be exhaustive orlimited to the embodiments disclosed. Many modifications and variationswill be apparent to those of ordinary skill in the art without departingfrom the scope and spirit of the described embodiments. The terminologyused herein was chosen to best explain the principles of theembodiments, the practical application or technical improvement overtechnologies found in the marketplace, or to enable others of ordinaryskill in the art to understand the embodiments disclosed herein.

What is claimed is: 1-9. (canceled)
 10. A system, comprising: a memorythat stores computer executable components; and a processor thatexecutes the computer executable components stored in the memory,wherein the computer executable component comprise: a data collectioncomponent that creates a master data block from a data entry blockchain,wherein the data entry blockchain comprises a group of data entry blocksthat are linked to each other, and wherein the master data blockcomprises a first header and data from the group of data entry blocks,wherein the header further comprises a first time stamp, an identifierthat identifies a source of the data, and a first hash based on thedata; and an analysis component that creates an analysis blockcomprising a log of an analysis performed on the data and a secondheader that comprises a second time stamp, a link to the master datablock, and a second hash based on the log of the analysis, wherein theanalysis block and the master data block comprise a blockchain.
 11. Thesystem of claim 10, wherein the computer executable components furthercomprise: an inspection component that creates a summary blockcomprising a summary of the data, a summary of the analysis and a resultof the analysis, and a third header comprising a link to the analysisblock.
 12. The system of claim 11, wherein the computer executablecomponents further comprise: a correction component that rates areliability of the result of the analysis based on the summary of theanalysis and the log of the analysis, wherein the reliability isassociated with a number of attempts to achieve the result of theanalysis.
 13. The system of claim 10, wherein the group of data entryblocks are retrieved from a public ledger database.
 14. The system ofclaim 10, wherein the link to the master data block in the analysisblock is the first hash.
 15. The system of claim 10, wherein the groupof data entry blocks are associated with respective data gatheringsessions. 16-20. (canceled)
 21. A system, comprising: a memory thatstores computer executable components; and a processor that executes thecomputer executable components stored in the memory, wherein thecomputer executable component comprise: a data collection componentthat: receives a first file having experimental data; generates a firstblock from the first file, wherein the first block comprises a firstheader and the experimental data, and wherein the header furthercomprises a first time stamp, an identifier that identifies a source ofthe experimental data, and a first hash based on the experimental data;and an analysis that generates a second block based on a second filethat comprises a log of an analysis performed on the experimental data,wherein the second block comprises the log of the analysis and a secondheader that comprises a second time stamp, a link to the first block,and a second hash based on the log of the analysis; and an inspectioncomponent that generates a third block comprising a summary of theexperimental data and the analysis and a result of the analysis.
 22. Thesystem of claim 21, wherein the inspection component also: joins thethird block to a blockchain associated with the first block and thesecond block by placing a link to the second block in a third header ofthe third block, and wherein the computer executable components furthercomprise: a correction component that rates a reliability of the resultof the analysis, wherein the reliability is based on the summary of theanalysis data and the log of the analysis and is associated with anumber of modifications to an analysis procedure.
 23. A computer programproduct to generate a blockchain using open scientific data, thecomputer program product comprising a computer readable storage mediumhaving program instructions embodied therewith, the program instructionsexecutable by a processor to cause the processor to: generate a masterdata block from a data entry blockchain, wherein the data entryblockchain comprises a group of data entry blocks that are linked toeach other, wherein the master data block comprises a first header anddata from the data entry blocks, and wherein the header furthercomprises a first time stamp, an identifier that identifies a source ofthe data, and a first hash based on the data; and generate an analysisblock comprising a log of an analysis performed on the data and a secondheader that comprises a second time stamp, a link to the master datablock, and a second hash based on the log of the analysis, wherein theanalysis block and the master data block comprise a blockchain.
 24. Thecomputer program product of claim 23, wherein the program instructionsare further executable to cause the processor to: generate a summaryblock comprising a summary of the data, a summary of the analysis and aresult of the analysis, and a third header comprising a link to ananalysis block entity graph is traversed to a depth based on a definedcriterion related to processing efficiency.
 25. The computer programproduct of claim 23, wherein the program instructions are furtherexecutable to cause the processor to: rate a reliability of the resultof the analysis based on the summary of the analysis and the log of theanalysis, wherein the reliability is associated with a number ofattempts to achieve the result of the analysis.